参数调整
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@ -98,14 +98,14 @@ if __name__ == "__main__":
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prvs = imgR # 上一帧的右画面,用于运动矢量计算
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# 每秒取5帧进行计算
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for frameID in range(round(cap.get(cv2.CAP_PROP_POS_FRAMES)), round(frameCount), round(frameRate/5)):
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if frameID >= frameCount:
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frameID -= 1
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for frameID in range(round(0), round(frameCount), round(frameRate/5)):
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if frameID >= frameCount - 3:
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frameID = frameCount - 3
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cap.set(cv2.CAP_PROP_POS_FRAMES, frameID)
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isSuccess, img = cap.read()
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if not isSuccess:
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print("video read error.")
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sys.exit()
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break
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# 分割左右画面
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imgL = np.split(img, 2, 1)[0]
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@ -125,14 +125,14 @@ if __name__ == "__main__":
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# 景深的平均值,偏大则意味着负视差(出屏感),可能不适
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AVG_depth = round(np.mean(disparity), 2)
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print("AVG depth: ", AVG_depth) # 大于0时开始不适,权重为0.15
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if AVG_depth > 0:
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print("AVG depth: ", AVG_depth) # 大于-10时开始不适,权重为0.15
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if AVG_depth > -10:
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comfort -= 0.15
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# 运动矢量大小的平均值,可判断画面大致上是否稳定
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AVG_motionMag = round(np.mean(hsv[..., 2]), 2)
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print("AVG motionMag: ", AVG_motionMag) # 大于30时略不适,权重0.1
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if AVG_motionMag > 30:
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print("AVG motionMag: ", AVG_motionMag) # 大于20时略不适,权重0.1
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if AVG_motionMag > 20:
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comfort -= 0.1
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# 景深的众数,由于景深基本不连续,众数意义不大
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@ -140,23 +140,23 @@ if __name__ == "__main__":
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# 运动矢量大小的众数,一般为0,若较大,说明画面中存在较大面积的快速运动,可能不适
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Mode_motionMag = stats.mode(hsv[..., 2].reshape(-1))[0][0]
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print("Mode motionMag: ", Mode_motionMag) # 大于0则不适,越大越不适,权重0.2,0到60归一化为0到0.15,大于60为0.2
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print("Mode motionMag: ", Mode_motionMag) # 大于0则不适,越大越不适,权重0.2,0到30归一化为0.1到0.15,大于60为0.2
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if Mode_motionMag > 0:
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if Mode_motionMag > 60:
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if Mode_motionMag > 30:
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comfort -= 0.2
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else:
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comfort -= Mode_motionMag/400
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comfort -= (Mode_motionMag/600 + 0.1)
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# 景深的标准差,若偏大说明景深范围较大,可能不适,但同时也是3D感更强的特征
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STD_depth = round(np.std(disparity),2)
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print("STD depth: ", STD_depth) # 大于150时略不适,权重为0.15
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if STD_depth > 150:
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print("STD depth: ", STD_depth) # 大于130时略不适,权重为0.15
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if STD_depth > 130:
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comfort -= 0.15
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# 运动矢量大小的标准差,若偏大说明各部分运动比较不一致,可能需要结合运动矢量的方向作进一步判断,若存在较复杂的运动形式,则可能不适
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STD_motionMag = round(np.std(hsv[...,2]),2)
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print("STD motionMag: ", STD_motionMag) # 大于30时略不适,权重为0.1
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if STD_motionMag > 30:
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print("STD motionMag: ", STD_motionMag) # 大于20时略不适,权重为0.1
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if STD_motionMag > 20:
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comfort -= 0.1
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# 运动矢量方向的标准差,若偏大说明各部分运动比较不一致,可能需要结合运动矢量的大小作进一步判断,若存在较复杂的运动形式,则可能不适
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@ -165,10 +165,10 @@ if __name__ == "__main__":
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disparity_Positive = disparity.copy()
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disparity_Positive[disparity_Positive < 0] = 0
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# 负视差的像素的所占比例,大于0.3时比较不适,权重0.15
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# 负视差的像素的所占比例,大于0.25时比较不适,权重0.15
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PCT_disparity_Positive = np.count_nonzero(disparity_Positive)/disparity_Positive.shape[0]/disparity_Positive.shape[1]
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print("close pixels percetage:", round(PCT_disparity_Positive,3))
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if PCT_disparity_Positive > 0.3:
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if PCT_disparity_Positive > 0.25:
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comfort -= 0.15
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# 存在运动的像素点的视差平均值
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@ -177,8 +177,8 @@ if __name__ == "__main__":
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movingPixels[movingPixels > 0] = 1
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movingDepth = np.multiply(disparity, movingPixels)
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AVG_movingDepth = round(np.sum(movingDepth)/np.count_nonzero(movingDepth))
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print("AVG movingDepth: ", AVG_movingDepth) # 大于10时不适,权重0.15
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if AVG_movingDepth > 10:
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print("AVG movingDepth: ", AVG_movingDepth) # 大于5时不适,权重0.15
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if AVG_movingDepth > 5:
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comfort -= 0.15
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framesComfort.append(comfort)
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@ -218,6 +218,7 @@ if __name__ == "__main__":
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# plt.pause(0.1)
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input("press Enter to continue")
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prvs = next # 当前帧覆盖上一帧,继续计算
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print("TotalFrameCalculated: ", framesCalculated)
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print("TotalComfort: ", round(sum(framesComfort)/framesCalculated,2))
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print("success")
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